When AWS returned to INRIX headquarters for Innovation Week in November last year, we brought more than a dozen team members. But the numbers don’t tell the whole story. Here’s what we’ve learned about partnerships: the second year reveals what the first year promised.
This year AWS didn’t just advise from the sidelines. We competed with our own team. We also embedded with two INRIX teams and focused on testing Amazon’s specific innovation methodologies of Working Backwards and Business Value.
Amazon’s Working Backwards mechanism starts with “who is the customer, and why will they care?”. Our approach to Business Value asks the question of “is investment worth it”? Taken together, these help teams avoid time and investment on solutions searching for a problem that may not really matter to customers.
The overall result: Six INRIX projects — 29% of all INRIX teams—organically integrated AWS services including: Amazon Bedrock, AgentCore, QuickSuite, and SageMaker.
The Moment of Insight
Consider what happened with the High Beam Engine project. We embedded with the team – helping pivot the project to start not from an INRIX product, but by identifying a particular customer with a specific problem and working backwards from there.
The team discovered something hiding in plain sight: much like the rest of the population, city traffic managers increasingly use LLM-driven chatbots and ‘search’ tools for information. Yet, INRIX expertise rarely surfaces in these AI-driven results. Your potential customers are asking questions for which INRIX has answers, but you’re not present much of the time you should be.
The potential solution? Transform INRIX’s marketing content creation into an AI-augmented approach that shifts from churning out content focused on search ‘rank’ to become the trusted answers AI (e.g. LLMs) recommend – showing up when it matters most, in the exact moment customers ask for help. The hypothesis for testing is straight forward: increase how often and positively AI systems cite INRIX and INRIX’s share of voice (AI) to drive more click-throughs, a larger and more relevant sales funnel, and more sales. Next up – time to solution and test key hypotheses around the potential business value to de-risk investment and increase ROI prospects for INRIX.
The Numbers That Matter
With 3D Hotspotters, we focused on Business Value and created tangible assets: an animated video and dynamic business value model INRIX sales can test with customers. The model reveals something compelling – assuming a trucking delivery company’s fleet travels at an average of 45 mph, each 1.0% improvement in average mph can reduce costs by $783k annually for a fleet of 1k trucks by helping them avoid signal and incident delays!( 1 )
What We Learned
Working alongside INRIX teams revealed transportation intelligence’s true complexity. Fifty petabytes of data – vehicle movements, parking patterns, crash analytics – all synthesized to power INRIX Compass. The hackathon exposed challenges we hadn’t fully grasped: data integration Durdles, prediction accuracy concerns, and the sheer orchestration required.
The learning flowed both ways. As your CPO Ahmed Darrat observed: “Amazon Quick Suite is like M365 CoPilot and Power BI on steroids.”
What Comes Next
Fore 2026 INRIX is interested in not only having an Innovation Week but also having an Implementation Week – turning prototypes into production solutions.
That pathway didn’t exist after last year. Now it does.
After five intensive days, we came away with deeper appreciation for what INRIX has built, a culture that creates dedicated space from bold ideas while maintaining operational excellence. The kind of environment where second collaborations reveal what first collaborations only hint at.
[1] A trucking delivery fleet with 1k trucks covering an average of 250 miles daily of delivery routes saves an estimated $783k annually by not reducing its average fleet speed from 45.53 to 45.00 mph) due to slowdowns.